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requirements and stringent power constraints are an explicit focus point of the group. NES-Lab focusses on design, analysis, and optimization of reliable and low-power embedded networks as a main building block
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network development. Experience with live-cell microscopy, fluorescence microscopy, or analysis of 3D/4D image data. Experience in cell biological or molecular biological laboratory work, particularly
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start date is October 2026. We recommend that you apply early as the advert may be removed before the deadline. Many technologies essential to a Net Zero future, including sustainable chemical processing
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maintaining national networks of geophysical instruments, and by operating a data center. The thesis will be conducted within the Waves and Structure Team, under the supervision of Nikolai Shapiro and Laurent
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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consequences of mineral extraction in the transition to net zero. Despite the global push toward decarbonisation, communities living in mineral‑rich regions often face exclusion from decision‑making, inequitable
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Transformer-Based Foundation Model for DNA Methylation in Longitudinal Cohorts.” The focus is on developing next-generation AI models for the analysis of DNA methylation. Using longitudinal data from, among
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will focus on the design and implementation of advanced models for data enhancement, denoising, semantic segmentation, content-based retrieval, target detection, multitemporal analysis, and radar mapping
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Symbolic AI, Neuro-Symbolic AI, Agentic AI, Neural Networks for code vulnerability detection (Senanayake et al. 2024), SBOM tools, prompt vulnerability detectors, and static/dynamic analysis tools could
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analysis of stakeholder networks across ministries, provinces, municipalities, water boards, and public health agencies Conducting AI-assisted evidence synthesis on integrated, cross-sectoral governance